Division of Systems Pharmacology and Pharmacy, Predictive Pharmacology Group, Leiden Academic Centre of Drug Research, Leiden University, Gorlaeus Laboratories, Leiden, the Netherlands.
Charles River Laboratories, Groningen, the Netherlands.
Eur J Pharm Sci. 2024 Dec 1;203:106883. doi: 10.1016/j.ejps.2024.106883. Epub 2024 Aug 22.
(AIM): K values are crucial indicators of drug distribution into the brain, representing the steady-state relationship between unbound concentrations in plasma and in brain extracellular fluid (brainECF). K values < 1 are often interpreted as indicators of dominant active efflux transport processes at the blood-brain barrier (BBB). However, the potential impact of brain metabolism on this value is typically not addressed. In this study, we investigated the brain distribution of remoxipride, as a paradigm compound for passive BBB transport with yet unexplained brain elimination that was hypothesized to represent brain metabolism.
(METHODS): The physiologically-based LeiCNS pharmacokinetic predictor (LeiCNS-PK model) was used to compare brain distribution of remoxipride with and without Michaelis-Menten kinetics at the BBB and/or brain cell organelle levels. To that end, multiple in-house (IV 0.7, 3.5, 4, 5.2, 7, 8, 14 and 16 mg kg) and external (IV 4 and 8 mg kg) rat microdialysis studies plasma and brainECF data were analysed.
(RESULTS): The incorporation of active elimination through presumed brain metabolism of remoxipride in the LeiCNS-PK model significantly improved the prediction accuracy of experimentally observed brainECF profiles of this drug. The model integrated with brain metabolism in both barriers and organelles levels is named LeiCNS-PK3.5.
(CONCLUSION): For drugs with K values < 1, not only the current interpretation of dominant BBB efflux transport, but also potential brain metabolism needs to be considered, especially because these may be concentration dependent. This will improve the mechanistic understanding of the processes that determine brain PK profiles.
（目的）：K 值是药物向大脑分布的关键指标，代表了血浆和脑细胞外液（brainECF）中未结合浓度的稳态关系。K 值<1 通常被解释为血脑屏障（BBB）中主动外排转运过程的指标。然而，通常未解决脑代谢对该值的潜在影响。在这项研究中，我们研究了罗美昔芬的脑分布，罗美昔芬是一种被动 BBB 转运的范例化合物，但其脑消除机制尚未阐明，据推测代表了脑代谢。
（方法）：使用基于生理的 LeiCNS 药代动力学预测器（LeiCNS-PK 模型）来比较罗美昔芬在 BBB 和/或脑细胞细胞器水平上具有和不具有米氏动力学时的脑分布。为此，分析了多个内部（IV 0.7、3.5、4、5.2、7、8、14 和 16 mg kg）和外部（IV 4 和 8 mg kg）大鼠微透析研究的血浆和 brainECF 数据。
（结果）：在 LeiCNS-PK 模型中纳入罗美昔芬的主动消除，通过假定的脑代谢，显著提高了该药物脑 ECF 谱的实验观察到的预测准确性。在两个屏障和细胞器水平上集成脑代谢的模型命名为 LeiCNS-PK3.5。
（结论）：对于 K 值<1 的药物，不仅要考虑当前对主导性 BBB 外排转运的解释，还要考虑潜在的脑代谢，特别是因为这些可能是浓度依赖性的。这将提高对决定脑 PK 谱的过程的机制理解。
